Sensor-Enabled Safety Systems for Human-Robot Collaboration: A Review

Abstract

Sensors are integrated into collaborative robot systems to ensure the safety of human workers by allowing them to perceive their environments, detect human presence, and adjust their actions accordingly. This preferred reporting items for systematic reviews and meta-analyses extension for scoping review (PRISMA-ScR) focuses on current sensor-enabled safety systems for human–robot collaboration (HRC) in the manufacturing industry based on both scientific papers and patents. From the initial search of 6669 references, 281 underwent full-text review and segmentation based on the sensor technology, installation location, and safety operating mode according to the ISO/TS 15066 standard. In the last decade, there has been a clear trend of increasing sensor-enabled safety systems. The dominant sensors used are infrared (IR)-structured light, capacitive, light detection and ranging (LiDAR), resistive, stereo/depth camera, RaDAR, and laser scanners. The primary safety operating mode identified was speed and separation monitoring (SSM). Some systems integrate multiple sensor types, with the most common combinations being LiDAR with stereo cameras or LiDAR with capacitive sensors, and laser scanners with RaDAR. We suggest multisensor integration and standardized benchmarks for future development. This review is among the few that employ the PRISMA-P protocol to study sensor technologies and contribute to a more systematic understanding of the current state of the art in this area.